This paper reviews the role of seasonality in shaping population dynamics of infectious diseases, focusing on both human and wildlife systems. Seasonal variations in temperature, rainfall, and resource availability can significantly influence host–pathogen interactions through various mechanisms, including changes in host behavior, contact rates, encounters with infective stages, annual pulses of host births and deaths, and shifts in host immune defenses. Empirical evidence and mathematical models demonstrate that seasonality can alter the spread and persistence of infectious diseases, leading to simple annual cycles or more complex multiyear fluctuations. Understanding the timing and causes of seasonality is crucial for forecasting long-term health risks, developing control strategies, and predicting disease risks in response to climate change. The paper highlights the importance of incorporating seasonal forcing into epidemiological models and identifies research priorities for improving our understanding of how seasonal variation modifies the population dynamics of infectious diseases.This paper reviews the role of seasonality in shaping population dynamics of infectious diseases, focusing on both human and wildlife systems. Seasonal variations in temperature, rainfall, and resource availability can significantly influence host–pathogen interactions through various mechanisms, including changes in host behavior, contact rates, encounters with infective stages, annual pulses of host births and deaths, and shifts in host immune defenses. Empirical evidence and mathematical models demonstrate that seasonality can alter the spread and persistence of infectious diseases, leading to simple annual cycles or more complex multiyear fluctuations. Understanding the timing and causes of seasonality is crucial for forecasting long-term health risks, developing control strategies, and predicting disease risks in response to climate change. The paper highlights the importance of incorporating seasonal forcing into epidemiological models and identifies research priorities for improving our understanding of how seasonal variation modifies the population dynamics of infectious diseases.